From 55755cef7fac125c0722ac396bde7a50394f90c3 Mon Sep 17 00:00:00 2001
From: Michel Lang <michellang@gmail.com>
Date: Mon, 20 Nov 2023 14:47:59 +0100
Subject: [PATCH] put all examples in dontrun for now

---
 man-roxygen/example.R                   | 2 ++
 man/mlr_learners_classif.cv_glmnet.Rd   | 2 ++
 man/mlr_learners_classif.glmnet.Rd      | 2 ++
 man/mlr_learners_classif.kknn.Rd        | 2 ++
 man/mlr_learners_classif.lda.Rd         | 2 ++
 man/mlr_learners_classif.log_reg.Rd     | 2 ++
 man/mlr_learners_classif.multinom.Rd    | 2 ++
 man/mlr_learners_classif.naive_bayes.Rd | 2 ++
 man/mlr_learners_classif.nnet.Rd        | 2 ++
 man/mlr_learners_classif.qda.Rd         | 2 ++
 man/mlr_learners_classif.ranger.Rd      | 2 ++
 man/mlr_learners_classif.svm.Rd         | 2 ++
 man/mlr_learners_classif.xgboost.Rd     | 2 ++
 man/mlr_learners_regr.cv_glmnet.Rd      | 2 ++
 man/mlr_learners_regr.glmnet.Rd         | 2 ++
 man/mlr_learners_regr.kknn.Rd           | 2 ++
 man/mlr_learners_regr.km.Rd             | 2 ++
 man/mlr_learners_regr.lm.Rd             | 2 ++
 man/mlr_learners_regr.nnet.Rd           | 2 ++
 man/mlr_learners_regr.ranger.Rd         | 2 ++
 man/mlr_learners_regr.svm.Rd            | 2 ++
 man/mlr_learners_regr.xgboost.Rd        | 2 ++
 22 files changed, 44 insertions(+)

diff --git a/man-roxygen/example.R b/man-roxygen/example.R
index 571eba99..3c2ceb1e 100644
--- a/man-roxygen/example.R
+++ b/man-roxygen/example.R
@@ -5,6 +5,7 @@ pkgs = setdiff(lrn$packages, c("mlr3", "mlr3learners"))
 #' <% task_id = if ("LearnerClassif" %in% class(lrn(id))) "sonar" else "mtcars" %>
 #'
 #' @examples
+#' \dontrun{
 #' if (<%= paste0("requireNamespace(\"", pkgs, "\", quietly = TRUE)", collapse = " && ") %>) {
 #' # Define the Learner and set parameter values
 #' <%= sprintf("learner = lrn(\"%s\")", id)%>
@@ -31,3 +32,4 @@ pkgs = setdiff(lrn$packages, c("mlr3", "mlr3learners"))
 #' # Score the predictions
 #' predictions$score()
 #' }
+#' }
diff --git a/man/mlr_learners_classif.cv_glmnet.Rd b/man/mlr_learners_classif.cv_glmnet.Rd
index b298432e..a5d5e93e 100644
--- a/man/mlr_learners_classif.cv_glmnet.Rd
+++ b/man/mlr_learners_classif.cv_glmnet.Rd
@@ -86,6 +86,7 @@ as the first factor level.
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("glmnet", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("classif.cv_glmnet")
@@ -113,6 +114,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \references{
 Friedman J, Hastie T, Tibshirani R (2010).
 \dQuote{Regularization Paths for Generalized Linear Models via Coordinate Descent.}
diff --git a/man/mlr_learners_classif.glmnet.Rd b/man/mlr_learners_classif.glmnet.Rd
index 7cb1b4be..3da0296c 100644
--- a/man/mlr_learners_classif.glmnet.Rd
+++ b/man/mlr_learners_classif.glmnet.Rd
@@ -95,6 +95,7 @@ as the first factor level.
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("glmnet", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("classif.glmnet")
@@ -122,6 +123,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \references{
 Friedman J, Hastie T, Tibshirani R (2010).
 \dQuote{Regularization Paths for Generalized Linear Models via Coordinate Descent.}
diff --git a/man/mlr_learners_classif.kknn.Rd b/man/mlr_learners_classif.kknn.Rd
index 7f386b5d..3dd36cac 100644
--- a/man/mlr_learners_classif.kknn.Rd
+++ b/man/mlr_learners_classif.kknn.Rd
@@ -62,6 +62,7 @@ lrn("classif.kknn")
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("kknn", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("classif.kknn")
@@ -89,6 +90,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \references{
 Hechenbichler, Klaus, Schliep, Klaus (2004).
 \dQuote{Weighted k-nearest-neighbor techniques and ordinal classification.}
diff --git a/man/mlr_learners_classif.lda.Rd b/man/mlr_learners_classif.lda.Rd
index 0e5338bb..6942e728 100644
--- a/man/mlr_learners_classif.lda.Rd
+++ b/man/mlr_learners_classif.lda.Rd
@@ -47,6 +47,7 @@ lrn("classif.lda")
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("MASS", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("classif.lda")
@@ -74,6 +75,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \references{
 Venables WN, Ripley BD (2002).
 \emph{Modern Applied Statistics with S}, Fourth edition.
diff --git a/man/mlr_learners_classif.log_reg.Rd b/man/mlr_learners_classif.log_reg.Rd
index 16029543..1091ac8d 100644
--- a/man/mlr_learners_classif.log_reg.Rd
+++ b/man/mlr_learners_classif.log_reg.Rd
@@ -83,6 +83,7 @@ Instead, set the respective hyperparameter or use \CRANpkg{mlr3pipelines} to cre
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("stats", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("classif.log_reg")
@@ -110,6 +111,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \seealso{
 \itemize{
 \item Chapter in the \href{https://mlr3book.mlr-org.com/}{mlr3book}:
diff --git a/man/mlr_learners_classif.multinom.Rd b/man/mlr_learners_classif.multinom.Rd
index 8b042495..d0c2b235 100644
--- a/man/mlr_learners_classif.multinom.Rd
+++ b/man/mlr_learners_classif.multinom.Rd
@@ -52,6 +52,7 @@ lrn("classif.multinom")
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("nnet", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("classif.multinom")
@@ -79,6 +80,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \seealso{
 \itemize{
 \item Chapter in the \href{https://mlr3book.mlr-org.com/}{mlr3book}:
diff --git a/man/mlr_learners_classif.naive_bayes.Rd b/man/mlr_learners_classif.naive_bayes.Rd
index 1aea0b73..8181ddcd 100644
--- a/man/mlr_learners_classif.naive_bayes.Rd
+++ b/man/mlr_learners_classif.naive_bayes.Rd
@@ -37,6 +37,7 @@ lrn("classif.naive_bayes")
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("e1071", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("classif.naive_bayes")
@@ -64,6 +65,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \seealso{
 \itemize{
 \item Chapter in the \href{https://mlr3book.mlr-org.com/}{mlr3book}:
diff --git a/man/mlr_learners_classif.nnet.Rd b/man/mlr_learners_classif.nnet.Rd
index d8fdca4b..0e147048 100644
--- a/man/mlr_learners_classif.nnet.Rd
+++ b/man/mlr_learners_classif.nnet.Rd
@@ -72,6 +72,7 @@ lrn("classif.nnet")
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("nnet", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("classif.nnet")
@@ -99,6 +100,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \references{
 Ripley BD (1996).
 \emph{Pattern Recognition and Neural Networks}.
diff --git a/man/mlr_learners_classif.qda.Rd b/man/mlr_learners_classif.qda.Rd
index 677632a8..439fb8bc 100644
--- a/man/mlr_learners_classif.qda.Rd
+++ b/man/mlr_learners_classif.qda.Rd
@@ -45,6 +45,7 @@ lrn("classif.qda")
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("MASS", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("classif.qda")
@@ -72,6 +73,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \references{
 Venables WN, Ripley BD (2002).
 \emph{Modern Applied Statistics with S}, Fourth edition.
diff --git a/man/mlr_learners_classif.ranger.Rd b/man/mlr_learners_classif.ranger.Rd
index d239e572..bca68095 100644
--- a/man/mlr_learners_classif.ranger.Rd
+++ b/man/mlr_learners_classif.ranger.Rd
@@ -88,6 +88,7 @@ lrn("classif.ranger")
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("ranger", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("classif.ranger")
@@ -115,6 +116,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \references{
 Wright, N. M, Ziegler, Andreas (2017).
 \dQuote{ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R.}
diff --git a/man/mlr_learners_classif.svm.Rd b/man/mlr_learners_classif.svm.Rd
index cd817879..ad539b3f 100644
--- a/man/mlr_learners_classif.svm.Rd
+++ b/man/mlr_learners_classif.svm.Rd
@@ -50,6 +50,7 @@ lrn("classif.svm")
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("e1071", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("classif.svm")
@@ -77,6 +78,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \references{
 Cortes, Corinna, Vapnik, Vladimir (1995).
 \dQuote{Support-vector networks.}
diff --git a/man/mlr_learners_classif.xgboost.Rd b/man/mlr_learners_classif.xgboost.Rd
index e9abcccb..ca5f8132 100644
--- a/man/mlr_learners_classif.xgboost.Rd
+++ b/man/mlr_learners_classif.xgboost.Rd
@@ -147,6 +147,7 @@ lrn("classif.xgboost")
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("xgboost", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("classif.xgboost")
@@ -173,6 +174,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 # Score the predictions
 predictions$score()
 }
+}
 
 \dontrun{
 # Train learner with early stopping on spam data set
diff --git a/man/mlr_learners_regr.cv_glmnet.Rd b/man/mlr_learners_regr.cv_glmnet.Rd
index 1ab38588..ba5c2b87 100644
--- a/man/mlr_learners_regr.cv_glmnet.Rd
+++ b/man/mlr_learners_regr.cv_glmnet.Rd
@@ -79,6 +79,7 @@ lrn("regr.cv_glmnet")
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("glmnet", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("regr.cv_glmnet")
@@ -106,6 +107,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \references{
 Friedman J, Hastie T, Tibshirani R (2010).
 \dQuote{Regularization Paths for Generalized Linear Models via Coordinate Descent.}
diff --git a/man/mlr_learners_regr.glmnet.Rd b/man/mlr_learners_regr.glmnet.Rd
index 2938319e..d41df9fd 100644
--- a/man/mlr_learners_regr.glmnet.Rd
+++ b/man/mlr_learners_regr.glmnet.Rd
@@ -95,6 +95,7 @@ lrn("regr.glmnet")
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("glmnet", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("regr.glmnet")
@@ -122,6 +123,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \references{
 Friedman J, Hastie T, Tibshirani R (2010).
 \dQuote{Regularization Paths for Generalized Linear Models via Coordinate Descent.}
diff --git a/man/mlr_learners_regr.kknn.Rd b/man/mlr_learners_regr.kknn.Rd
index 48346ecb..42b4e3f5 100644
--- a/man/mlr_learners_regr.kknn.Rd
+++ b/man/mlr_learners_regr.kknn.Rd
@@ -62,6 +62,7 @@ lrn("regr.kknn")
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("kknn", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("regr.kknn")
@@ -89,6 +90,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \references{
 Hechenbichler, Klaus, Schliep, Klaus (2004).
 \dQuote{Weighted k-nearest-neighbor techniques and ordinal classification.}
diff --git a/man/mlr_learners_regr.km.Rd b/man/mlr_learners_regr.km.Rd
index 79ac415f..27c7401f 100644
--- a/man/mlr_learners_regr.km.Rd
+++ b/man/mlr_learners_regr.km.Rd
@@ -71,6 +71,7 @@ lrn("regr.km")
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("DiceKriging", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("regr.km")
@@ -98,6 +99,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \references{
 Roustant O, Ginsbourger D, Deville Y (2012).
 \dQuote{DiceKriging, DiceOptim: Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization.}
diff --git a/man/mlr_learners_regr.lm.Rd b/man/mlr_learners_regr.lm.Rd
index f9ac44ab..1c47b9f4 100644
--- a/man/mlr_learners_regr.lm.Rd
+++ b/man/mlr_learners_regr.lm.Rd
@@ -60,6 +60,7 @@ Instead, set the respective hyperparameter or use \CRANpkg{mlr3pipelines} to cre
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("stats", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("regr.lm")
@@ -87,6 +88,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \seealso{
 \itemize{
 \item Chapter in the \href{https://mlr3book.mlr-org.com/}{mlr3book}:
diff --git a/man/mlr_learners_regr.nnet.Rd b/man/mlr_learners_regr.nnet.Rd
index 7fa81f08..67bb4061 100644
--- a/man/mlr_learners_regr.nnet.Rd
+++ b/man/mlr_learners_regr.nnet.Rd
@@ -72,6 +72,7 @@ lrn("regr.nnet")
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("nnet", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("regr.nnet")
@@ -99,6 +100,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \references{
 Ripley BD (1996).
 \emph{Pattern Recognition and Neural Networks}.
diff --git a/man/mlr_learners_regr.ranger.Rd b/man/mlr_learners_regr.ranger.Rd
index f980e806..8b7e383e 100644
--- a/man/mlr_learners_regr.ranger.Rd
+++ b/man/mlr_learners_regr.ranger.Rd
@@ -88,6 +88,7 @@ Note that \code{mtry} and \code{mtry.ratio} are mutually exclusive.
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("ranger", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("regr.ranger")
@@ -115,6 +116,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \references{
 Wright, N. M, Ziegler, Andreas (2017).
 \dQuote{ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R.}
diff --git a/man/mlr_learners_regr.svm.Rd b/man/mlr_learners_regr.svm.Rd
index 73f29da4..d6d8af70 100644
--- a/man/mlr_learners_regr.svm.Rd
+++ b/man/mlr_learners_regr.svm.Rd
@@ -48,6 +48,7 @@ lrn("regr.svm")
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("e1071", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("regr.svm")
@@ -75,6 +76,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 predictions$score()
 }
 }
+}
 \references{
 Cortes, Corinna, Vapnik, Vladimir (1995).
 \dQuote{Support-vector networks.}
diff --git a/man/mlr_learners_regr.xgboost.Rd b/man/mlr_learners_regr.xgboost.Rd
index e162d45e..386fb73d 100644
--- a/man/mlr_learners_regr.xgboost.Rd
+++ b/man/mlr_learners_regr.xgboost.Rd
@@ -146,6 +146,7 @@ would error. Just setting a nonsense default to workaround this.
 }
 
 \examples{
+\dontrun{
 if (requireNamespace("xgboost", quietly = TRUE)) {
 # Define the Learner and set parameter values
 learner = lrn("regr.xgboost")
@@ -172,6 +173,7 @@ predictions = learner$predict(task, row_ids = ids$test)
 # Score the predictions
 predictions$score()
 }
+}
 
 \dontrun{
 # Train learner with early stopping on spam data set